Wireless communication systems experience a demand for higher end-user data rates and increased system capacity. Some examples of solutions to increase the system capacity include using existing spectrum resources more efficiently, using additional spectrum resources, increasing the spatial reuse of (existing and/or additional) spectrum (i.e. adding more cells to the system in a denser network node deployment), and various combinations of these three solutions.
For example, extreme system capacity requirements may be a result of a high amount of users demanding a high average data rate, a situation with high traffic density in a geographical area that may typically occur in urban environments. To support such traffic demands, dense or very dense network deployment may be considered.
In dense network node deployment, there typically occur situations when a wireless communication device experiences Line-of-Sight (LoS) conditions in relation to more than one base station (or other network node). LoS conditions may be defined in any conventional way. For example, LoS conditions may refer to a delay spread of the channel from a base station being lower than a LoS threshold and/or a ratio between a peak (e.g. power, energy, magnitude, or similar) and another metric of a channel characteristic being above a ratio threshold, wherein the another metric may comprise an average value or a second largest value or similar among the other values of the channel characteristic (e.g. power delay profile or another suitable delay profile).
A dense network scenario may be defined as a scenario when a wireless communication device experiences LoS conditions (or very close to LoS conditions) in relation to a number of network nodes, wherein the number exceeds a dense network scenario threshold. The dense network scenario threshold may for example be set to a number between 3 and 6, e.g. to 3, 4, 5 or 6, According to another definition, a dense network scenario may be defined as a scenario when a wireless communication device experiences LoS conditions (or very close to LoS conditions) with a received signal strength exceeding a signal strength threshold in relation to a number of network nodes, wherein the number exceeds a dense network scenario threshold. The dense network scenario threshold may, for example, be set as above and the signal strength threshold may, for example, be set to a number between −60 and −80 dBm (for example, for a system with 5 MHz bandwidth and where the received signal strength is measured as a RSSI value), e.g. to −60, −70 or −80 dBm.
In a typical example urban environment with tall or very tall buildings laid out in a Manhattan-type street grid, network nodes (e.g. serving macro cells) may be deployed on roof top level and additional network nodes (e.g. serving micro, pico or femto cells) may be deployed at street level or inside buildings. For example, macro cell nodes may be deployed on roof tops of approximately half of the blocks, and micro cell nodes may be deployed in e.g. each street crossing. In such a dense or very dense deployment, a wireless communication device will often experience LoS conditions in relation to a number of network nodes.
For example, FIG. 1 illustrates a dense network scenario in a Manhattan-type street grid according to some embodiments. In part (a) of FIG. 1 a side view of four high-rise buildings 1, 2, 3, 4 is provided. In parts (b) and (c) of FIG. 1 top views of 16 high rise buildings (of which four correspond to the four buildings in part (a)) are provided.
Macro cell nodes 11, 12, 13, 14, 15, 16, 17, 18 are deployed on roof tops of some of the buildings as illustrates in part (a) and (b) and micro nodes 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56 are deployed on street level on two sides of each building as illustrated in part (a) and (c).
At a high elevation (e.g. a level as illustrated by 63 and by part (b)) the macro cells are dominant and at a low elevation (e.g. a level as illustrated by 61 and by part (c)) the micro cells are dominant. At a medium elevation (e.g. a level as illustrated by 62) the impact of micro and macro cells may be considered similar.
A wireless communication terminal residing in or around building 2 at high elevation may experience LoS conditions to many or all of the macro cell nodes 11-18, and a wireless communication terminal residing in or around building 2 at low elevation may experience LoS conditions to many or all of the micro cell nodes 22, 23, 26, 27, 30, 31, 34, 35, and 41-48 (illustrated by filled circles in part (c) of FIG. 1.
A dense network scenario situation typically offers a challenging radio environment for a wireless communication device to operate in. For example, the isolation between cells near cell borders will be poor and, more generally, a geometry factor describing the difference between the best cell path gain and the sum of the path gain from all other neighboring cells will typically be low.
In a capacity limited situation at full traffic load in an interference limited network, the geometry factor may be equal to a wideband SINR (Signal to Interference and Noise Ratio) before antenna combining at the wireless communication device. However, in contrast to a data-plane SINR measure, the geometry factor is independent of the actual load and interference levels.
For data-plane considerations in dense network scenarios, data communication may be enhanced by transmission and reception coordination methods (e.g. Coordinated Multi Point transmission/reception—CoMP) when a wireless communication device is connected to several cells. Such solutions typically cannot be applied for control-plane considerations, e.g. measurements of Reference Signal Received Power (RSRP) and/or Reference Signal Received Quality (RSRQ) based on Cell-specific Reference Symbols (CRS) to be used by Radio Resource Management (RRM) algorithms. This is due to that CRS and other relevant signaling is always transmitted. Hence, interference problems cannot be solved by coordinated transmission.
RRM measurements are an important functionality of a wireless communication device. It is, for example, used to determine which cell to camp on or connect to. Thus, RRM measurements need to be based on a robust design. A typical robust design of RRM measurements includes considering worst case scenarios of e.g. Doppler spread (channel variation in time domain), delay spread (channel variation in frequency domain) and SINR. However, such a generally robust design limits the performance for some specific scenarios. For example, using a generally robust design in dense network scenarios may lead to the RRM measurements limiting the benefits (e.g. capacity increase) of the dense network deployment, since the generally robust approach does not result in high enough accuracy of the RRM measurements and, hence, the RRM algorithms (e.g. cell selection, handover, etc) becomes sub-optimally executed.
Therefore, there is a need for alternative radio resource measurement approaches in dense network scenarios.